The authors have developed an autonomous loading system for a wheel loader. In this paper, an algorithm is proposed to decide on both an optimized unloading point and several paths between the unloading point and several scooping points. The optimal unloading point that minimizes the total length of those paths has been obtained by using a three-dimensional configuration score space. In the configuration score space, the length of the route from origin to each grid is represented as score number, and a grid shows a position(x,y) and posture(θ). This method was evaluated through simulations and by experiments using a miniature wheel loader robot.

We propose a method to recognize cups on desks and to detect liquids in cups with a depth camera using triangulation. When we measure an opaque liquid in a cup with the depth camera, the liquid surface is measured. On the other hand, when we measure a transparent liquid, the raised bottom is measured due to the principle of light refraction and triangulation. We formulated it theoretically, and confirmed that the theory is consistent with the experimental results. Therefore, it is possible to detect the existence of liquids in cups using the measured height based on this theory. In our experiments, the proposed method have successfully detected various transparent or opaque liquids.

This paper presents an approach for vehicle localization in the mountainous non-paved roads of a quarry. First, the elaboration of a 3D elevation map using data from dead reckoning, RTK-GPS and a laser sensor is described, where an extended Kalman filter was used for state and covariance estimation. Terrain traversability analysis is performed and scan points are voted in an elevation map which is probabilistically built and updated. Secondly, the vehicle's pose is estimated using a particle filter correcting the position towards the elevation map where GPS information is not used. Finally, experiments were performed in the mountainous gravelled paths of a quarry. Estimated localization results compared towards centimeter precision GPS show that the system offers sub-meter precision.

This paper reports an experimental system of autonomous omni directional mobile tables and their automatic rearrangement. This system 1. detects the position of meeting tables using a camera on ceiling, 2. makes a route from the detected position by a motion planning and 3. arranges the table robots to the desired positions. We developed 4 table robots as multiple omni-directional mobile robots and constructed a position detecting system using LEDs (Light Emitting Diode) attached on the tables. A camera is fixed on the ceiling. We also developed a motion planning algorithm for the robots. Consequently, the table robots can move from an arbitrary arrangement to an arbitrary arrangement. The effectiveness of the proposed algorithm was confirmed.

The goal of rescue robotics is to extend the capabilities and to increase the safety of human rescue teams. During a rescue mission a mobile robot is deployed on a rescue site and is operated from a safe place by a human operator. The operator can not see the robot and the environment and a decision on the path selection is very complicated. Our goal is to provide a kind of automatic “pilot system” to propose an operator a good direction or several options to traverse the environment, taking into an account the robot's static and dynamic properties. To find a good path we need a special path search algorithm on debris and a proper definition of a search tree, which can ensure smooth exploration. While the main goal of the algorithm is to keep the robot maximally stable at every step of its path, in some cases we need the robot to lose its balance and to change a 3D orientation discontinuously. Losing balance on purpose is an important feature for safe climbing up and going down the debris and it is the central issue of this paper. Exhaustive simulations were used to structure and analyze data and experiments were used to verify our approach to removing unsuitable directions of the search from the search tree.

The objective of this research is to perform a long distance navigation in indoor environment, with a unicycle robot that has a wide-type wheel, and has a laser range finder installed on top of the robot. At present, there is no report for long distance navigation by unicycle robot in real indoor environment. We have developed a system that consists of two subsystems; “Balancing and Maneuvering System” for moving robot to desired direction while the posture of the robot is stabilized, and “Navigation System” for calculation of desired direction and recognition of intersections, using external sensor whose scan plain changes when robot steers. We have implemented the system to a single SH-4 CPU microcomputer, and performed a long distance navigation in actual indoor environment. The paper reports the unicycle robot and the system we have developed, and the experiment result of long distance navigation in indoor environment.

This paper presents an approach for vehicle 3D localization in outdoor woodland environments using a loosely coupled multisensor system. The vehicle 3D dead reckoning is computed using a wheel encoder and an IMU. Dead reckoning is corrected from three different sources: a) using a tilted lidar for road detection and computation of the vehicle position within the road which is then corrected towards a 2D road centerline map given in advance. b) DGPS 2D or 3D data as available. c) Under tree foliage DGPS blackouts commonly occur, specially when measuring height, therefore the use of a barometer for correcting height is proposed. An extended Kalman filter is used for sensor fusion and pose estimation. Finally, the estimated vehicle height is added to the 2D map obtaining a 3D road centerline map with width (measured by the tilted lidar). Thoroughly experimentation on real mountainous woodland paths show the usefulness and robustness of the proposed approach.

This paper describes a 2D localization method for a differential drive mobile vehicle on real forested paths. The mobile vehicle is equipped with two rotary encoders, Crossbow’s NAV420CA Inertial Measurement Unit (IMU) and a NAVCOM SF-2050M GPS receiver (used in StarFire-DGPS dual mode). Loosely-coupled multisensor fusion and sensor fault detection issues are discussed as well. An extended Kalman Filter (EKF) is used for sensor fusion estimation where a GPS noise pre-filter is used to avoid introducing biased GPS data (affected by multi-path). Normalized Innovation Squared (NIS) tests are performed when a GPS measurement is incorporated to reject GPS data outliers and keep the consistency of the filter. Finally, experimental results show the performance of the localization system compared to a previously measured ground truth.

This paper investigates a collision-free navigation algorithm for a mobile robot to work in daily environment which includes multiple walking people. The proposed algorithm consists of two main parts: recognizing walking people and collision-free path planning. For the recognition of randomly changing human walking motion, a people tracking method using laser range finder (LRF) is utilized. Robust people tracking could be achieved by embedding a new biped model with a walking frequency tracker, which can estimate the frequency of human walking motion and generate it continuously even in the case of no measurement owing to occlusion. For the other part, collision-free path planning, an iterative forecast and planning method with the concept of configuration space including space and time is employed. The position and velocity of walking people, given from people tracking algorithm, are exploited in path planning part as the information of obstacles that the robot have to avoid. The proposed method has been implemented on a real robot. It is also demonstrated with some experiments the tracking of multiple walking humans and robot navigation in indoor environment.

This paper presents and describes the approach for achieving long distance autonomous navigation with a mobile robot on outdoor cluttered pedestrian paths. The task was to finish an event launched by the City of Tsukuba in Japan, called “RealWorld Robot Challenge”, of navigating 1km autonomously in a real environment with real pedestrians and bicycles. The hardware, software and strategy for navigating in cluttered environments is explained. Moreover, the complementary functionality of the overall system where map-based and sensor-based navigation seamlessly change, is presented. The robustness of the system is validated with experimental results.

This paper proposes fast map building algorithm for multiple modal exteroceptive(external) sensors based on trajectory optimization. To realize localization using multiple modal exteroceptive sensors needs consistent environment maps (landmark maps). Multiple sensor SLAM (simultaneous localization and mapping) is one of solutions to build maps consistently. In implementation of SLAM, approximations of sensor model contribute to get speeded up the algorithm. However in several case, these approximations deteriorate quality of the map. This paper proposes fast and accurate map building algorithm using multiple modal sensors based on sparse linear equations solver. This algorithm needs less approximations-but computation speed is fast. In addition, application of measured data from multiple sensors to this algorithm is described.

In this paper we present a systematic study of the performance of seven different configurations of GPS on a moving vehicle using three different GPS receivers. The seven different configurations are 1) single frequency code differential DGPS, 2) double frequency code differential DGPS, 3) RTK-GPS receiving RTCM correction from a mobile phone, 4) RTK-GPS receiving RTCM correction information via wireless module from base antenna, 5) StarFire WADGPS, 6) StarFire-DGPS dual mode and 7) StarFire-RTK GPS dual mode. As GPS is mostly used in loosely coupled configurations where receiver output is fused with other sensors, the contribution of this paper is the statistical comparison in two dimensions of different GPS configurations using as performance index availability, precision (using standard deviation parameters of each measurement) and reliability. Two types of study environments were tested, open sky and under tree shading. Time for re-acquiring fix solution for RTK-GPS configurations and re-acquiring dual frequency solution by dual frequency configurations are discussed as well. Finally, experimental measurement results show how under tree shading, biased position data with small covariance can be rejected thresholding measurements with small HDOP values and large number of satellites used for solution.

This paper introduces a planning method for handling furniture which exists in real world. We propose a method which is easily expandable its handle able furniture such as closet, shelf and so on. If the robot can handle such furniture autonomously, it is expected that multiple daily tasks, for example, storing a small object in a drawer, can be achieved by the robot. Because perplexing processes is needed to give the knowledge of furniture handling to the robot manually, we propose direct teaching based approach which can easily give not only how to handle the furniture but also an appearance and 3D shape of it. Combining general knowledge given in advance and manipulation procedure instructed by human directly, the robot acquires how to manipulate the storing places. The performance of the proposed method is illustrated by experiments.

The present authors take such an approach to build a service mobile robot that all the robot functions are categorized into common functions and specific functions. The common functions are assigned to a mobile robot and the specific functions are assigned to a specific mechanism. A "portable effector" is designed for a mechanism to accomplish the specific task. The portable effector is placed on the floor near the task space in the environment. A navigation and docking functions with the effector provided as common functions for the mobile robot. The robot changes the portable effector automatically according to the assigned task. In this paper, the authors describe techniques of automatic docking with portable effector for the mobile robot. They include position alignment technique proper to docking by PWS type mobile robot using simple sensor and mark, and firm holding mechanism between the robot and the effector. The docking mechanism is designed so as to allow alignment error at the time of docking. The authors illustrate portable effector changing operation using two kinds of portable effectors in the real environment

This paper describes a grasp planning for a mobile manipulator which works in real environment. Mobile robot studies up to now that manipulate an object in real world practically use ID tag on an object or an object model which is given to the robot in advance. The authors aim to develop a mobile manipulator that can acquire an object model through video images and can manipulate the object. In this approach, the robot can manipulate an unknown object autonomously. A grasp planning proposed in this paper can find a stable grasp pose from the automatically generated model which contains redundant data and the shape error of the object. Experiments show the effectiveness of the proposed method

To monitor multiple moving objects from a robot in motion is an essential technology in robotic application areas including service and security for human daily life. For this, a method to track multiple walking humans using a mobile robot "in motion" with laser range finder (LRF) is investigated in this paper. Geometric characteristics of human legs are considered to detect their position from the LRF data. Frequency and phase of walking motion are extracted using a pendulum model of the angle between two legs and extended Kalman filter. The algorithm with human walking model anticipates the position of moving humans. The effectiveness of the proposed method is also evaluated with some experiments to track multiple walking humans in indoor environment. An experimental testbed which consists of a mobile robot "Yamabico" and a LRF is employed to track people. Resultant experiments and analysis showed that multiple walking people are tracked well from a mobile robot with the proposed method

A 3D scan matching is an important component for sensor based localization and mapping by a mobile robot in natural environment. In this paper, the present authors propose a way to extend 2D normal distributions transform (NDT) scan matching method to 3D scan matching, and its improvement for faster processing time. This scan matching method divides scan into voxels, and approximates scan points in each cell into normal distribution. That matching time is O(N) with N of the number of input scan points. The authors describe in this paper, NDT for 3D scan points, its acceleration using the dual resolutions of NDT, and experiments of map building in large scale environments

This paper describes motion planning for a mobile manipulator which works in real environment. Mobile manipulators that can manipulate an object was developed up to now. We assume that object grasping is not restricted to just one grasp way and robot can move freely as far as it is in its operational area of the object. This paper proposes the motion planning for object grasping under the previous explained conditions. There are two major issues to detect the robot pose. The first problem is pose error of the robot hand. The second problem is kinematical redundancy of the mobile manipulator. The pose is evaluated from the amount of joint motions for recovery of hand pose error. Experiments show the effectiveness of the proposed method.

Our group developed a method of path generation for wheel loaders as part of our ongoing research on the autonomous loading operation of wheel loaders at surface mines and construction sites. The path connecting the present vehicle position and scooping position consists of clothoid curves and straight lines. Each line segment is optimized in a path generation procedure. A simplified model of the pile shape and bucket trajectory is used to determine the scooping direction based on an estimation of the resistance force applied on the bucket during the scooping motion. We applied the proposed method in an experimental model. A stereo-vision system was used to measure the shape of the pile and the scooping direction that imposed the least moment on the bucket was selected as the scooping position. This method generates an appropriate path for the wheel loader.

The final objective of the authors is to realize mobile robot navigation in walkway of outdoor environment. The path along the walkway which is measured correctly together with landmarks must be given in the framework in this paper. The robot identifies its position by means of odometry, DGPS and laser range finder (LRF) during the motion along the path. This work contributes to the map building of landmarks along the walkway. To make the map, RTK-GPS, odometry and LRF are used for the sensory devices and Kalman smoothing technique is also incorporated to interpolate trajectory of the scanning LRF equipment between the two point that RTK-GPS measurement took place. The scanning by LRF is performed to acquire the 3-D shape of objects along the walkway. The trajectory presumed properly and well organized shapes of the objects are reconstructed.

This paper describes 3-D shape modeling performed by a mobile robot. We propose a method in which the robot in the real environment acquires the accurate shape and constructs a 3-D model of an object using Computer Vision techniques under the condition that position and shape of the object is unknown. 3-D modeling is performed from image streams which are captured by a camera placed on the robot. The results show the effectiveness of our method.

It is important and necessary to develop a teleoperated mobile robot to have reconnaissance operation inside of the extreme earthquake stricken building or underground town. The present authors aim at developing such a teleoperated mobile robot. In this paper, a prototype of the teleoperation and man-robot interface system is proposed. The tele-operated robot and the remote operation station is linked with wireless network and the operator can command the robot. One feature point of this system is to provide a live omni-directional panoramic view image and live map to the operator on the display of the remote operation station. The live map represents the floor plan of the moving environment and it is provided by SLAM technology with LRF scan data. It proves very effective to have combined use of the panoramic image and the live map. Experimental set up and integrated experiments are also reported in this paper.

This paper describes how to acquire 3-D shape of an object and to estimate robot pose by observing an unknown object. A single camera is placed on the robot, image streams of the target object are captured by the camera on a mobile robot moving around the object. Computer vision techniques are utilized under the condition that shape, size and accurate position information of the target object is not given in advance, but the robot finds the target object and reconstructs the 3-D object shape by itself. In addition, it is necessary that the robot grasps relative pose between itself and the target object. Experimental result show the effectiveness of our method in point of robustness and accuracy for the mobile robot.

The authors aim at map based outdoor navigation of a mobile robot. In navigation, robot position is fundamentally obtained by odometry. However, the position is misaligned as the robot moves because odometry has cumulative error. DGPS measurement data may cancel its position error. The framework of EKF is used for the modification and the fusion between odometry and DGPS measurement data. The DGPS measurement data, however, could have large error because of multipath near buildings. In this paper, the authors propose a method which eliminates erroneous DGPS measurement data when odometry robot position is fused, and confirm the validity of this approach.

This paper presents a novel design of indoor airship having a passive wheeled mechanism and its stationary position control. This wheeled blimp can work both on the ground using wheeled vehicle part and in the air using the floating capability of the blimp part. The wheeled blimp stands on the floor keeping its balance using a caster-like passive wheel mechanism. In tele-guidance application, stationary position control is required to make the wheeled blimp naturally communicate with people in standing phase since the stationary blimp system responds sensitively to air flow even in indoor environments. To control the desired stationary position, a computed torque control method is adopted. By performing a controller design through dynamic analysis, the control characteristics of the wheeled blimp system have been found and finally the stable control system has been successfully developed. The effectiveness of the controller is verified by experiment for the real wheeled blimp system.

This paper describes a strategy of a mobile robot walkway following using color image. There are different colors in a walkway and lawn area alongside the walkway. The walkway area is extracted by an image processing. Color difference among walkway and waysides is considered in the image processing. Robustness against daylight change for segmentation of walkway area is also considered. The robot moves to the direction toward vanishing point of the walkway which is obtained from the image processing. Repeating these processes, the walkway following can be accomplished.

A quantitative evaluation method of manipulative difficulty for a tractor pushing or towing multiple trailers is introduced. A manipulative difficulty index (MDI) thinking about imperfect measurement is proposed. This difficulty varies if physical parameters such as the position of the joint or the number of the trailers is changed. The authors focus on this change when some state variables have measurement errors. Also, quantitative comparisons for typical examples of the change of physical parameters of tractor-trailers under the above case are presented.

This paper describes a strategy of a mobile robot walkway following using color image. There are different colors in a walkway and lawn area along side the walkway. The walkway area is extracted by an image processing using the difference of color. The robot moves to the direction of vanishing point which is obtained from the image processing. Repeating these processes, the walkway following will be accomplished.

This research work contributes to an active vision system for an gas pipe inspection robot moving inside of the pipe. The robot must be able to know what shape of the pipes where the robot is moving. The shapes of the pipe include straight, L or T. Also, when it is moving in the straight section, the robot must detect the relative angle with respect to its principal axis. The authors propose to use a laser spot array and TV camera for the vision sensor, which can find the three dimensional position of each spot on the surface of the pipe by means of triangulation. The shape of the pipe inside can be reconstructed by the information of the camera. A method is also presented to distinguish the shape whether it is straight or not.

The index of the manipulative difficulty for a mobile robot towing and pushing multiple trailers to follow a straight line is proposed. It will be useful to design such a tractor-trailers system. Some examples of the manipulative difficulty index was calculated by changing the number of trailers when the mobile robot pushes and tows the trailers.

We propose a new mechanism of a unicycle. One feature of this robot is the shape of the wheel which is similar to a rugby ball. The other feature is that the body is separated into upper and lower parts. We give the details of a mechanism of the robot, simple controller system, and some results of a performance experiment using the designed controller. We present experimental results that show that the robot can move in a straight line and steer itself by the proposed mechanism.

We are interested in the operation facilities of vehicle that are simple even for persons who are not experienced in vehicle operation. One idea simplifying the vehicle operation is to separate the operation from the mechanism of the vehicle. In this system, the human operator specifies a temporary goal position of the mobile robot by touching the monitor in which front view images are displayed. The robot then travels toward this goal position. The path to the goal position is generated by the system and shown on the front view images. Therefore, the operator need not practice how to operate steering wheel or accelerator. We have constructed an experimental setup and evaluated it by controlling the robot.

We propose a practical approach which allow a tractor-trailer robot to plan and navigate a path, considering its shape and its kinematics constraint, however, without generating the configuration space for the sized robot. The operator can choose his preference of forward or backward paths by motion cost assignments. The path is generated in three stages: 1) road map analysis, 2) robot's states and transitions states generation, and 3) path search and motions generations. The planner has been tested on a tractor-trailer robot using different trailer sizes, demonstrating its ability for automatic generation of path, which may include even backward motions.

A map in mobile robotics plays an important role. The mobile robot is vested with a sense of geographical understanding by such a knowledge base for its intelligent behavior. This article is a short survey of map generation for mobile robots. The present author gives a summary of related research works in all the proceedings of IROS until now, and he presents nowadays trends.

This paper presents an algorithm which leads a mobile robot to its destination in an environment where multiple obstacles are moving around. The movement of each obstacle is forecasted under the assumption that it moves with a piecewise constant velocity. Based on the forecast, a feasible path for a robot is searched in (x,y,t) space by a heuristic method. The robot follows feasible path for a while. This path is composed of straight lines and circular curves. To accommodate the actual changes in the obstacles' velocity against the forecast, the forecast and path searching is iterated frequently while the robot is moving to the goal. This paper examines the behavior obtained by different experimental conditions in the computer simulations.

This paper investigates behavior of a single mobile robot which is navigated by an "iterated forecast and planning" scheme in an environment where multiple obstacles are moving around. This navigation scheme, which was previously proposed by the authors, searches a feasible path for a robot in (x,y,t) space by a heuristic method. The movement of each obstacle is then forecasted under the assumption that it moves with a piecewise constant velocity. The planning algorithm is iterated frequently to accommodate the actual changes in the obstacles' velocity. This paper examines various kinds of the behavior obtained by different experimental conditions in the computer simulations.>

Estimation of the position based on a conventional dead-reckoning for a mobile robot intrinsically contains cumulative errors. In relation to this, large nonzero probability of its error distribution is occasionally found even outside the workspace, because the dead-reckoning takes no account of the unreachability outside the workspace. This paper presents a new fusion algorithm for dead-reckoning, in which both the dead-reckoned position and the knowledge of the closed workspace are fused by means of Bayesian inference. This algorithm produces zero probability outside the workspace theoretically. Through a computer simulation, the effectiveness of the proposed algorithm is confirmed.>

This paper addresses the problem of navigation for a single mobile robot in an environment of multiple moving obstacles. It presents a near learning algorithm extension to a previously reported (nonlearning) planner. This combined planning system performs the two complementary functions: (1) it derives most feasible velocity of the robot under forecasts for the movements of obstacles in space-time, and (2) it stores obstacle state and feasible velocity values for future reference. Motion planning to derive a feasible velocity of the robot and movement according to the velocity are iterated at regular short intervals. If the robot is confronted with the same situation that is memorized before, the memorized velocity of the robot corresponding to the situation will be used. The algorithm's performance is demonstrated with data from computer simulations.

This paper describes an efficient algorithm of path planning for an internal gas pipe inspection robot. Since the purpose of this robot is to move in pipes to detect injures and scratches, the path should cover all pipes in a given map. The problem to find a path along which the robot can investigate all pipes at least so that the total distance is minimum is called 'Chinese Postman Problem'. Usually this problem is NP-complete. If all values of pipes are non-negative, the numerical programming is applied for finding the optimal path. However this is still too complicated to apply for searching the path. Motivated by this motivation, a method to find the optimal path based on the A* algorithm is proposed, which is treated more easily than the numerical programming. Finally some numerical simulation results are presented.

The authors have constructed a self-contained intelligent robot on which ultrasonic range finders are installed. A sensory system with sensing ability appears necessary; the authors propose a vision system for a mobile robot that meets real time requirements. In the vision system, a color image provids actual image information and map information is also utilized for reckoning in a building environment. The key point is that matching between image and map information is performed by using highly abstracted information from the image and also from the map. The constitution of the vision system and experimental results are described.